| --- |
| license: other |
| license_name: qwen-research |
| base_model: Qwen/Qwen-Image-2.1 |
| library_name: diffusers |
| pipeline_tag: text-to-image |
| tags: |
| - qwen |
| - image-generation |
| - image-editing |
| - rgba |
| - lora |
| - distilled |
| - few-step |
| --- |
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| <div align="center"> |
|
|
| <h1 style="color: #9334E9;">β‘ Qwen-Image-2.1-P-Turbo</h1> |
|
|
| <h2>Few-step LoRA adapters for Qwen-Image-2.1</h2> |
|
|
| <h3> |
| <span style="color: #9334E9;">5 or 8 steps</span> |
| Β· |
| <span style="color: #9334E9;">No CFG</span> |
| Β· |
| Text-to-image and image editing |
| </h3> |
|
|
| </div> |
|
|
| **Qwen-Image-2.1-P-Turbo is a set of LoRA adapters that let |
| [`Qwen/Qwen-Image-2.1`](https://huggingface.co/Qwen/Qwen-Image-2.1) generate |
| and edit images in only 5 or 8 steps. The adapters load on top of the base |
| model, so the pipeline, text encoder and VAE stay unchanged. Training is based |
| on DMD. Improved using Qwen.** |
|
|
| > **v0.1: first release, work in progress.** P-Turbo does not yet match the |
| > visual quality of the base model. We are still improving the distillation and |
| > will update this repository as new versions become available. |
|
|
| ## Examples |
|
|
|
|
| ## Variants |
|
|
| Both adapters are v0.1. Pick one based on whether you need quality or speed. |
|
|
| | File | Steps | Trade-off | |
| |---|:---:|---| |
| | `p_qwen_image_2.1_8step_v0.1.safetensors` | 8 | **Higher quality.** Recommended as the default. | |
| | `p_qwen_image_2.1_5step_v0.1.safetensors` | 5 | **Higher speed**, with noticeably lower visual quality. | |
|
|
| Each adapter is trained for its own sigma schedule. Load only one at a time. |
|
|
| ## Quickstart |
|
|
| Runs text-to-image and image editing with the same pipeline. Needs a **CUDA GPU**. |
|
|
| ```bash |
| pip install 'torch>=2.4.0' 'transformers>=5.17' accelerate peft pillow |
| pip install git+https://github.com/huggingface/diffusers@6256aa7666cedd47443adc8f82da9a10e110b09c |
| ``` |
|
|
| ```python |
| import torch |
| from PIL import Image |
| from diffusers import FlowMatchEulerDiscreteScheduler, QwenImage21Pipeline |
| |
| STEPS = 8 # 8 for higher quality, 5 for higher speed |
| |
| # The terminal sigma 0 is appended by the scheduler. |
| SIGMAS = { |
| 5: [1.0, 0.94, 6 / 7, 2 / 3, 0.4], |
| 8: [1.0, 14 / 15, 6 / 7, 10 / 13, 2 / 3, 6 / 11, 0.4, 2 / 9], |
| }[STEPS] |
| |
| pipe = QwenImage21Pipeline.from_pretrained( |
| "Qwen/Qwen-Image-2.1", torch_dtype=torch.bfloat16 |
| ).to("cuda") |
| pipe.load_lora_weights( |
| "PrunaAI/Qwen-Image-2.1-P-Turbo", |
| weight_name=f"p_qwen_image_2.1_{STEPS}step_v0.1.safetensors", |
| ) |
| |
| # Use the sigmas exactly as given: no extra shifting. |
| pipe.scheduler = FlowMatchEulerDiscreteScheduler.from_config( |
| pipe.scheduler.config, |
| use_dynamic_shifting=False, |
| shift=1.0, |
| shift_terminal=None, |
| ) |
| |
| settings = dict( |
| num_inference_steps=STEPS, |
| sigmas=SIGMAS, |
| true_cfg_scale=1.0, |
| use_kv_cache=False, |
| ) |
| ``` |
|
|
| ## For Text-to-Image |
|
|
| Longer, more descriptive prompts give better results. |
|
|
| ```python |
| image = pipe( |
| prompt=( |
| 'A glowing neon shop sign that reads "QWEN IMAGE 2.1", mounted on a brick wall ' |
| "in a narrow city alley at night. Heavy rain, wet pavement reflecting pink and " |
| "blue light, shallow depth of field, cinematic photograph." |
| ), |
| width=1024, |
| height=1024, |
| generator=torch.Generator("cuda").manual_seed(42), |
| **settings, |
| ).images[0] |
| image.save("t2i_example.png") |
| ``` |
|
|
| ### For Image Editing |
|
|
| ```python |
| image = pipe( |
| prompt="Change the background to a sunset beach", |
| image=Image.open("input.png").convert("RGB"), |
| generator=torch.Generator("cuda").manual_seed(42), |
| **settings, |
| ).images[0] |
| image.save("edit_example.png") |
| ``` |
|
|
| ## Recommended settings |
|
|
| - **Use the sigma schedule that matches your adapter**, and keep the scheduler |
| at `shift=1.0` with dynamic shifting off so the sigmas are not shifted twice. |
| - 8-step: `1 β 14/15 β 6/7 β 10/13 β 2/3 β 6/11 β 0.4 β 2/9 β 0` |
| (shift 2, computed as `Ο = 2t / (1 + t)` on evenly spaced `t`) |
| - 5-step: `1 β 0.94 β 6/7 β 2/3 β 0.4 β 0` |
| - **No CFG.** Keep `true_cfg_scale=1.0` and do not pass a negative prompt. |
| - **Keep the LoRA strength at 1.0.** |
| - **Write detailed prompts for text-to-image.** Longer prompts that describe |
| the subject, setting, lighting and style work noticeably better than short |
| ones. |
| |
| ## Limitations |
|
|
| - This is a first version. Quality is below that of the base model. |
| - The 5-step adapter is faster than the 8-step one, but its images are |
| visibly worse. |
| - Short or vague text-to-image prompts give weaker results. |
| - The adapters are only intended for the settings above. Other step counts, |
| schedules or CFG values are not supported. |
|
|
| ## What this is not |
|
|
| - Not a standalone model. It needs the `Qwen/Qwen-Image-2.1` base weights. |
| - Not a replacement for the base model when you need its full quality. |
| - Not a finished release. Expect the weights to change in future versions. |
|
|
| ## License |
|
|
| Qwen-Image-2.1-P-Turbo is a derivative of Qwen-Image-2.1 and is distributed |
| under the **Qwen RESEARCH LICENSE AGREEMENT**. Review its use restrictions |
| before using or redistributing the adapters. |
|
|
| Qwen is licensed under the Qwen RESEARCH LICENSE AGREEMENT, Copyright (c) 2026 |
| Hangzhou Tongyi Laboratory Technology Co., Ltd. All Rights Reserved. |
|
|
| ## What's next? |
|
|
| - **Use P-Turbo to generate and edit images with Qwen-Image-2.1 in a few steps.** |
| - Compress your own models with [Pruna](https://github.com/PrunaAI/pruna) and give us a βοΈ for more efficiency! |
| - Want to use our optimized image models right away? Check [P-Image-Ideogram](https://www.pruna.ai/p-image-ideogram) and [P-Image-Edit](https://www.pruna.ai/p-image-edit). |
|
|
| <style> |
| .model-button { |
| display: inline-flex; |
| flex-direction: row; |
| justify-content: center; |
| align-items: center; |
| gap: 8px; |
|
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| padding: 8px 20px; |
| border: none; |
| border-radius: 8px; |
|
|
| background: #9334e9; |
| color: #ffffff; |
|
|
| font-size: 14px; |
| font-weight: 400; |
| line-height: 1; |
| text-decoration: none; |
| white-space: nowrap; |
| cursor: pointer; |
|
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| box-sizing: border-box; |
| overflow: visible; |
| opacity: 1; |
| } |
| </style> |
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